The concept of virtual channels is well known, for example as disclosed by WO-02/080552 and WO-00/40021. These channels enable easy navigation through and management of recorded programs as well as their recording and deletion on a personal video recorder (PVR). Personalized content channels are channels whose content is not solely defined by a broadcaster. In certain virtual channel systems, each personalized content channel is defined by a boolean filter that operates typically on the metadata associated with the input content item (TV program) which is derived from an electronic program guide (EPG) such that only those content items whose metadata satisfy this filter are included on the personalized content channel. It is inherently multi-user oriented, as each user can define his own set of channels, without requiring explicit user identification.
Although the filters are capable of defining dedicated channels, they are, as such, not particularly suited for a more refined tuning towards the specific taste of the user or users of a personalized content channel, as this is a task of greater complexity. For example, a personalized content channel may have romantic dramas recorded on disk, but the user might only watch some of them, whereas others seem to be of less interest to the user. Finding out the differences between these two categories of movies is generally not easy and, in particular, possibly unknown to the user.
Certain virtual channel systems use a recommender to determine which content items to play out in a virtual channel. TV-program recommenders are becoming increasingly popular in PVRs such as TiVo to provide a more personalized service by learning the preferences of a user (or group of users), for example, by maintaining and analyzing watching behavior, and, based on these preferences, recommend or automatically record programs of interest to the user(s). In comparison with boolean filters, recommenders are less predictable, i.e. can provide a user with surprising suggestions.
Such a recommender system, however, suffers from the drawback that it must be able to do user identification, e.g., by a log-in procedure or by using face recognition, to ensure which user is operating the device and who's preferences to use.